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A correction was published on 24 June 2014, see Sensors 2014, 14(6), 11277.

Sensors 2014, 14(4), 5768-5780; doi:10.3390/s140405768
Article

Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

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Received: 7 January 2014 / Revised: 10 February 2014 / Accepted: 15 March 2014 / Published: 25 March 2014
(This article belongs to the Section Remote Sensors)
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Abstract

Land surface temperature (LST) is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS). This paper presents an adjustment of the split window algorithm (SWA) for TIRS that uses atmospheric transmittance and land surface emissivity (LSE) as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE) of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.
Keywords: thermal remote sensing; TIRS; Landsat-8; land surface temperature thermal remote sensing; TIRS; Landsat-8; land surface temperature
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Rozenstein, O.; Qin, Z.; Derimian, Y.; Karnieli, A. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm. Sensors 2014, 14, 5768-5780.

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